Our environment is always buzzing with energetic, smart, and motivated people who have a bias for action and truly believe in the core purpose and our values.
What is the role?
Within the Data Science unit, our core purpose is creating intelligence for a healthier tomorrow by leveraging our vast data to drive valuable insights to improve both clinical and operational environments. Key to our purpose is obtaining and structuring quality data, leveraging cutting edge analytical innovations and delivering actionable insights in a sustainable and meaningful way. We leverage an integrated, collaborative, and multidisciplinary approach to ensure our objectives and goals are met.
The role entails architecting the data platform layer, data cleansing layer, reporting and analytical layers. Work closely with Data Scientists to understand model features and link back to transactional environment to understand data quality, data relationships and data availability. Document and define frameworks with the Data Engineer to build the data platform. Together these teams will enable data driven actionable insights. The role may include international exposure with partnerships.
What You Will Do
The successful applicant will be working within a highly specialized and growing team to enable delivery of data and advanced analytics system capability.
Responsibilities Will Include
- Provide Data Architecture (DA) support for the Data Engineering team.
- Expert documentation of DA for new data sources, metadata, and productionized information flow
- Work closely with Data Engineer to facilitate Data Governance including access and security control.
- Work closely with the Data Engineers and Data Scientists to facilitate automated Data Quality checks and model drifts.
- Build, design, and constant revision of the Model Execution Framework
- Define DA for the Data Science teams and participate in review and walk-through sessions for model fit and model productionisation.
- Assist with the definition of custom meta data models for ELT/ETL
- Direct data automation capabilities with the Data Engineer and Data Scientist
- Profile new data sources in a variety of formats including JSON, XML, etc.
- Define data quality rules with Data Scientists to clean data.
- Define data mapping and transformation rules between source and data warehouse and data lake.
- Documentation using Confluence/Wiki
- Solution design and system analysis
- Data profiling
- Strong communicator verbally and in writing
- Expert database knowledge in SQL
- Modern data warehouse design skills
- Exceptional data modelling skills i.e., physical, dimensional, and relational 3N forms, using Ralph Kimball methodology.
- Experience working on large and complex datasets.
- DevOps/DataOps and CI/CD experience.
- Strong leader
- A passion for data
- A passion for documentation of solutions
- Highly analytical and critical thinker
- Self-starter
- Willingness to learn and grow exponentially.
- A restless curiosity in learning new technology
- Ability to work cohesively in a team environment and balance multiple priorities.
- A team player who can work alone when required and without supervision.
- High level of attention to detail, resilience, enthusiasm, energy, and drive
- Positive, can-do attitude
- Ethical and able to maintain confidentiality and manage boundaries.
- Professional Qualifications & Experience
- Degree/Diploma in Engineering or Software Engineering with solid experience in data architecture
- Other qualifications will also be considered if accompanied by the relevant experience.
Eligibilities:
